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作 者:谢祥宸 XIE Xiangchen(School of Electronic and Information Engineering,Hebei University,Baoding 017100,China)
机构地区:[1]河北大学电子信息工程学院,河北保定017100
出 处:《河南科技》2025年第6期17-21,共5页Henan Science and Technology
摘 要:【目的】为保证电力系统稳定运行,提高运维效率,设计并实现一种集成大数据技术、人工智能技术和物联网技术的电力变压器故障诊断与智能预警系统。【方法】首先,部署多种传感器实时收集变压器运行数据信息;其次,利用物联网技术实现数据传输与存储;再次,利用大数据技术和人工智能算法深度挖掘和处理数据,实现精确预测和故障预警;最后,设计用户友好型界面,为运维人员进行故障排查和处理以及动态性掌握变压器运行状态提供方便。【结果】该电力变压器故障诊断与智能预警系统能有效预警变压器运行故障,并对变压器展开实时监测。相较于传统的方法,该系统在监测方面使用多样化手段,可以快速、准确诊断故障,提高预警的及时性,提高管理质量。【结论】该系统对提升电力系统智能化水平、保障电网安全稳定运行具有积极作用。[Purposes]This study aims to design and implement a power transformer fault diagnosis and intelligent early warning system that integrates big data technology,artificial intelligence technology and Internet of Things technology,so as to enhance the operation and maintenance efficiency and stable operation capability of power system.[Methods]Firstly,a variety of sensors were deployed to dynamically collect transformer operation data information;secondly,Internet of Things technology was used to record,transmit and store data;then big data technology and artificial intelligence algorithm were used to deeply mine and process data to accurately predict and timely warn faults;finally,the user-friendly interface is designed to provide convenience for operation and maintenance personnel to dynamically grasp the running state of the transformer,and carry out effective troubleshooting and processing.[Findings]The power transformer fault diagnosis and intelligent early warning system developed in this study can effectively warn transformer operation faults and carry out real-time monitoring.Compared with the traditional methods,the designed and developed system uses a variety of monitoring methods to improve the timeliness of early warning,accurately diagnose faults and improve management quality.[Conclusions]The system has positive significance for improving the intelligent level of power system and ensuring the safe and stable operation of power grid.
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